Macs in Chemistry

Insanely Great Science


I first mentioned alvaScience in a review of alvaDesc I wrote in 2019 Since then I've mentioned new products as they have been launched but only recently have I gone back to the website to look at things in more detail.

At alvaScience, we are constantly exploring and implementing the most promising and innovative technologies in our software tools, which makes them a leading choice for QSAR and other cheminformatics research.

alvaModel is an interesting software tool to create Quantitative Structure Activity/Property Relationship (QSAR/QSPR) models using the descriptors and fingerprints calculated in alvaDesc. It comes with a variety of very useful tools for data and descriptors, such as feature reduction and a variety of machine learning tools

Regression model

  • Ordinary Least Squares (OLS) model
  • Partial Least Squares (PLS) model
  • KNN regression model
  • Support Vector Machine (SVM) model
  • Consensus model defined as the arithmetic mean of the values predicted by the selected models

Classification model

  • Linear and Quadratic Discriminant Analysis (LDA/QDA) model
  • Partial Least Squares Discriminant Analysis (PLS-DA) model
  • KNN classification model
  • Support Vector Machine (SVM) model
  • Consensus model defined assigning the class based on the majority of the values predicted by the selected models

Whilst building models is one thing being able to deploy them easily is something else. alvaRunner helps with this. alvaRunner can be accessed via the command line but I suspect many users will use the graphical interface. Using the GUI, for every imported molecule, you can see the predicted targets and whether the molecule is inside or outside the defined model’s Applicability Domain and you can sort and filter any column by right-clicking the corresponding column header.


alvaScience will be at the RSC-SCI Workshop on Computational Tools for Drug Discovery 2022, if you would like to try it out why not come along.

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